• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.927-935
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• 2005

The certainty factors of the fuzzy production rules and the certainty factors of fuzzy propositions appearing in the rules are represented by real values between zero and one. If it can allow the certainty factors of the fuzzy production rules and the certainty factors of fuzzy propositions can be represented by intervals, such as vague numbers between zero and one based on vague sets, then it can allow the reasoning of rule-based systems to perform fuzzy reasoning in more flexible manner[18]. we are also proposed an efficient algorithm to perform vague set reasoning automatically. This vague set reasoning algorithm allows the rule-based systems to perform reasoning in a more flexible and more efficient.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.11-35
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• 1995

In this paper the fuzzy extension for the classical engineering mechanics problems is studied. The governing differential equation is derived for the buckling loads of the columns with uncertain mediums: the their own weight and the flexural rigidity. The columns with one typical end constraint(hinged1 clarnped/free) and the other finite rotational spring with fuzzy constant are considered in numerical examples. The vertex method is used to evaluate the fuzzy functions. The Runge-Kutta method and Determinant Search method are used to solve the differential equation and determine the buckling loads, respectively. The membership functions of the buckling load are calculated. The index of fuzziness to quantitatively describe the propagation of fuzziness is defined. According to the fuzziness of governing factors, the varlation of index of fuzziness for buckling load is investigated, and the sensitivity for the end constraints is analyzed.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.611-618
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• 2003

In this paper, we describe a fuzzy inference approach for detecting and classifying shot transitions in video sequences. Our approach basically extends FAM (Fuzzy Associative Memory) to detect and classify shot transitions, including cuts, fades and dissolves. We consider a set of feature values that characterize differences between two consecutive frames as input fuzzy sets, and the types of shot transitions as output fuzzy sets. The inference system proposed in this paper is mainly composed of a learning phase and an inferring phase. In the learning phase, the system initializes its basic structure by determining fuzzy membership functions and constructs fuzzy rules. In the inferring phase, the system conducts actual inference using the constructed fuzzy rules. In order to verify the performance of the proposed shot transition detection method experiments have been carried out with a video database that includes news, movies, advertisements, documentaries and music videos.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.203-209
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• 2016

In this paper, we introduce a fuzzy inference systems for nonlinear inference using fuzzy cluster. Typically, the generation of fuzzy rules for nonlinear inference causes the problem that the number of fuzzy rules increases exponentially if the input vectors increase. To handle this problem, the fuzzy rules of fuzzy model are designed by dividing the input vector space in the scatter form using fuzzy clustering algorithm which expresses fuzzy cluster. From this method, complex nonlinear process can be modeled. The premise part of the fuzzy rules is determined by means of FCM clustering algorithm with fuzzy clusters. The consequence part of the fuzzy rules have four kinds of polynomial functions and the coefficient parameters of each rule are estimated by using the standard least-squares method. And we use the data widely used in nonlinear process for the performance and the nonlinear characteristics of the nonlinear process. Experimental results show that the non-linear inference is possible.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.115-119
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• 1997

본 논문은 색료의 삼원색인 빨강, 노랑 및 파랑을 적절히 혼합하는 경우에 나타나는 색채를 추론하는 문제에 대하여, 퍼지이론을 적용하여 결과를 추론하는 문제를 다루고 있다. 즉, 인간이 색료의 혼합에 있어서 행하는 과정을 모사한 퍼지규칙을 바탕으로 삼원색의 색료가 일정 분량씩 혼합된 경우, 결과적으로 나타나는 색을 직접 실험을 통하지 않고 추론할 수 있는 시스템을 구축하고 있다. 또한, 구축된 시스템에 대하여 여러 가지 예를 통한 모의 실험을 수행하여 본 연구에서 구축된 색채혼합 시스템의 타당성을 검증하였다.

• Fire Science and Engineering
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• v.18 no.4
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• pp.42-51
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• 2004

This paper presents a study on the analysis of fire detection system using fuzzy logic with input variables of temperature and smoke density. The input variables for the fuzzy logic algorithm are measured by fire experiment of small scale with temperature detector and smoke detector. The antecedent part of fuzzy rules consists of temperature and smoke density, and the consequent part consists of fire possibility. Also the triangular fuzzy membership function is chosen for input variables and fuzzy rules to simplify computation. In order to calculate fuzzy values of such fuzzy system, a computer program is developed with Matlab based on graphics user interface. The experiment was conducted with paper and ethanol to simulate flaming fire and with plastic and sawdust to model smoldering fire. The results showed that the fire detection system presented here was able to diagnose fire very precisely. With the help of algorithms using fuzzy logic we could distinguish whether fire or not.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.48-55
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• 2011

In this paper, we analyze the input-output characteristics of fuzzy inference systems according to the division of entire input spaces and the fuzzy reasoning methods to identify the fuzzy model for nonlinear process. And fuzzy model is expressed by identifying the structure and parameters of the system by means of input variables, fuzzy partition of input spaces, and consequence polynomial functions. In the premise part of the rules Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the hard clusters are used for identification of fuzzy model and membership function is used as a series of triangular membership function. In the consequence part of the rules fuzzy reasoning is conducted by two types of inferences. The identification of the consequence parameters, namely polynomial coefficients, of the rules are carried out by the standard least square method. And lastly, we use gas furnace process which is widely used in nonlinear process and we evaluate the performance for this nonlinear process.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.174-179
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• 1995

본 논문데서는 부하외란이나 시스템 내부 파라미터의 변동시에 적응력이 저하되는 종래의 PI제어기와, 정상상태 잔류편차가 존재하는 퍼지 제어기의 단점을 극복하기 위한 적 응 퍼지 제어 기법을 제안하였고, 이를 도립 진자 시스템에 적용하였다. 운송차의 위치 및 진자 각도의 오차, 오차의 변화량에 따라 퍼지 추론을 행하여 PI 제어기의 가중치를 결정하 는 구조로, P제어기는 운송차 및 진자의 오차가 과도 상태에서의 영역에서 사용되어 속응성 과 고정도의 특성을 얻는다. 1제어기는 정상상태에서의 정도 향상에 이용되었다. 특히, 제안 하는 적응 퍼지 제어기는 운송차의 위치 오차에 대한 PI 동작과, 진자의 각도 오차에 대한 PI 동작을 각각 퍼지 추론에 의해 부드럽게 전환함으로서 고유 불안정의 시스템인 도립 진 자 시스템의 안정화 제어에 적용하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.4
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• pp.18-32
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• 1995

Fuzzy rules, developed by experts thus far, may be often inconsistent and incomplete. This paper proposes a new methodology for automatic generation of fuzzy rules which are nearly complete and not inconsistent. This is accomplished by simulating a knowledge gathering process of humans from control experiences. This method is simpler and more efficient than existing ones. It is shown through simulation that our method even generates better rules than those generated by experts, under fine tuned parameters.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.431-434
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• 2002

본 논문에서는 온라인 신문을 보는 사용자의 취향을 평가하고 취향에 맞는 인터페이스를 추천하는 시스템을 제안한다 신문사, 분류, 키워드 등의 평가요소에 대한 사용자 데이터의 중요도를 이용해 퍼지 측도$\square$적분으로 취향을 평가하여 해당되는 인터페이스를 제공한다. 또한 추천 받은 인터페이스에 대한 사용자의 만족도를 요소의 선택 빈도와 기사 읽은 시간 그리고 읽은 기사의 수로부터 추론하여 평가하고, 추론된 만족도에 의해 중요도를 변경시킴으로써 변화하는 사용자의 취향에 적응하는 시스템을 제안한다.